Tina Vartziotis

Lara Vartziotis, Tina Vartziotis, Frank Beutenmueller et al.

In remote and hybrid work contexts, the integration of physical and digital environments is revolutionizing spatial experiences, collaboration, and interpersonal interactions. This study examines three fundamental spatial conditions: the physical environment, characterized by material and sensory attributes; the virtual environment, influenced by immersive technologies; and their fusion into hybrid environments where digital and physical components interact dynamically. The increasing number of AI tools in contemporary society, extensively utilized in both professional and personal spheres, has led to a varied landscape of developing technologies. For instance, ChatGPT has emerged as one of the most downloaded applications, a statistically substantiated fact that demonstrates the swift incorporation of language-based AI into daily life. It also underscores the function of large language models (LLMs) as meaningful bridges between concepts at reading emotional and behavioral signals via natural language. These models provide real-time modifications such as altering illumination, acoustics, or interface configurations, converting static settings into dynamic, emotionally receptive environments. We investigate the integration of language models into professional settings and their potential to enhance user experience by promoting focus, well-being, and engagement. The study investigates ethical concerns, including privacy, emotional tracking, and user agency, emphasizing the importance of inclusive and transparent design. This research formulates a framework for creating co-adaptive environments that merge technological innovation with human-centered experiences, offering a fresh viewpoint on responsive and supportive hybrid workspaces.

Tina Vartziotis, Ippolyti Dellatolas, George Dasoulas et al. · harvard

The increasing use of information technology has led to a significant share of energy consumption and carbon emissions from data centers. These contributions are expected to rise with the growing demand for big data analytics, increasing digitization, and the development of large artificial intelligence (AI) models. The need to address the environmental impact of software development has led to increased interest in green (sustainable) coding and claims that the use of AI models can lead to energy efficiency gains. Here, we provide an empirical study on green code and an overview of green coding practices, as well as metrics used to quantify the sustainability awareness of AI models. In this framework, we evaluate the sustainability of auto-generated code. The auto-generate codes considered in this study are produced by generative commercial AI language models, GitHub Copilot, OpenAI ChatGPT-3, and Amazon CodeWhisperer. Within our methodology, in order to quantify the sustainability awareness of these AI models, we propose a definition of the code's "green capacity", based on certain sustainability metrics. We compare the performance and green capacity of human-generated code and code generated by the three AI language models in response to easy-to-hard problem statements. Our findings shed light on the current capacity of AI models to contribute to sustainable software development.

Lara Vartziotis, Tina Vartziotis, Valentin Keckeisen et al.

This paper explores the intersection of memory, place, and identity, examining how new technologies, particularly Apple Vision Pro, can illuminate this nexus. Leveraging digital twins and virtual reality, it investigates how memory is woven into landscapes and urban environments of cultural and historical significance, identifying visual elements that evoke memory and heritage. Applications such as Apple Vision Pro can facilitate image extension to define place identity, informing viewers about cultural and political entities across timelines. Visual storytelling can showcase the evolution of landscapes and the preservation of cultural heritage, while Virtual Reality (VR) enables the recreation of historical landscapes and urban-scapes. This immersive approach invites users to transcend temporal boundaries and experience the past dynamically. Semantic Image Search can support research by uncovering images related to monuments, tradition, or cultural identity. This research introduces a methodology to connect digital twins and virtual environments with urban and non-urban landscapes to illustrate cultural, historical, and environmental sustainability. Central to this approach is defining the resilience of the current state, its future evolution, and the significance of the past. These technologies facilitate a historical and cultural embrace while evoking the feeling of returning to a specific place years later. The methodology outlines the integration of technologies needed to revitalize public urban places through cultural and political memory. Through these applications, this paper contributes to research on digital twins of spaces, urban transformation, and cultural heritage preservation. By offering insights into the relationship between memory, place, and identity in the digital age, it supports a deeper understanding of our collective past and its impact on the present.